Overview

Dataset statistics

Number of variables18
Number of observations1053
Missing cells1072
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory203.8 KiB
Average record size in memory198.2 B

Variable types

Numeric16
Categorical1
Unsupported1

Alerts

Sex is highly overall correlated with hematocrit_percent and 1 other fieldsHigh correlation
cd4_count_cells_uL is highly overall correlated with hiv_vl_copies_mLHigh correlation
hematocrit_percent is highly overall correlated with Sex and 1 other fieldsHigh correlation
hemoglobin_g_dL is highly overall correlated with Sex and 1 other fieldsHigh correlation
hiv_vl_copies_mL is highly overall correlated with cd4_count_cells_uLHigh correlation
lymphocyte_count_10e9_L is highly overall correlated with wbc_count_10e9_LHigh correlation
mch_pg is highly overall correlated with mchc_g_dL and 1 other fieldsHigh correlation
mchc_g_dL is highly overall correlated with mch_pgHigh correlation
mcv_fL is highly overall correlated with mch_pgHigh correlation
monocyte_count_10e9_L is highly overall correlated with wbc_count_10e9_LHigh correlation
neutrophil_count_10e9_L is highly overall correlated with wbc_count_10e9_LHigh correlation
wbc_count_10e9_L is highly overall correlated with lymphocyte_count_10e9_L and 2 other fieldsHigh correlation
study_week has 1053 (100.0%) missing valuesMissing
study_week is an unsupported type, check if it needs cleaning or further analysisUnsupported
eosinophil_count_10e9_L has 47 (4.5%) zerosZeros
basophil_count_10e9_L has 122 (11.6%) zerosZeros

Reproduction

Analysis started2025-11-25 06:48:47.245384
Analysis finished2025-11-25 06:48:57.095962
Duration9.85 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

Age (at enrolment)
Real number (ℝ)

Distinct45
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.460589
Minimum13
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.120664image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile21
Q127
median32
Q337
95-th percentile46
Maximum62
Range49
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.7363651
Coefficient of variation (CV)0.23833101
Kurtosis0.1552562
Mean32.460589
Median Absolute Deviation (MAD)5
Skewness0.52185785
Sum34181
Variance59.851345
MonotonicityNot monotonic
2025-11-25T08:48:57.165997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
3166
 
6.3%
3356
 
5.3%
2955
 
5.2%
3053
 
5.0%
3250
 
4.7%
2649
 
4.7%
3548
 
4.6%
3448
 
4.6%
2447
 
4.5%
2847
 
4.5%
Other values (35)534
50.7%
ValueCountFrequency (%)
131
 
0.1%
141
 
0.1%
152
 
0.2%
171
 
0.1%
189
 
0.9%
198
 
0.8%
2017
1.6%
2119
1.8%
2226
2.5%
2331
2.9%
ValueCountFrequency (%)
621
 
0.1%
591
 
0.1%
572
 
0.2%
552
 
0.2%
544
0.4%
535
0.5%
523
0.3%
517
0.7%
504
0.4%
492
 
0.2%

Sex
Categorical

High correlation 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size64.0 KiB
Female
627 
Male
426 

Length

Max length6
Median length6
Mean length5.1908832
Min length4

Characters and Unicode

Total characters5466
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMale
2nd rowMale
3rd rowMale
4th rowFemale
5th rowFemale

Common Values

ValueCountFrequency (%)
Female627
59.5%
Male426
40.5%

Length

2025-11-25T08:48:57.214912image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-25T08:48:57.252412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
female627
59.5%
male426
40.5%

Most occurring characters

ValueCountFrequency (%)
e1680
30.7%
a1053
19.3%
l1053
19.3%
F627
 
11.5%
m627
 
11.5%
M426
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4413
80.7%
Uppercase Letter1053
 
19.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1680
38.1%
a1053
23.9%
l1053
23.9%
m627
 
14.2%
Uppercase Letter
ValueCountFrequency (%)
F627
59.5%
M426
40.5%

Most occurring scripts

ValueCountFrequency (%)
Latin5466
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1680
30.7%
a1053
19.3%
l1053
19.3%
F627
 
11.5%
m627
 
11.5%
M426
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII5466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1680
30.7%
a1053
19.3%
l1053
19.3%
F627
 
11.5%
m627
 
11.5%
M426
 
7.8%

BMI (kg/m²)
Real number (ℝ)

Distinct1016
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.11742
Minimum15.269471
Maximum49.672814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.291554image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum15.269471
5-th percentile17.880777
Q120.15625
median23.084852
Q326.794938
95-th percentile33.960395
Maximum49.672814
Range34.403343
Interquartile range (IQR)6.638688

Descriptive statistics

Standard deviation5.3163571
Coefficient of variation (CV)0.2204364
Kurtosis2.3289041
Mean24.11742
Median Absolute Deviation (MAD)3.2616416
Skewness1.2722863
Sum25395.643
Variance28.263653
MonotonicityNot monotonic
2025-11-25T08:48:57.343037image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.805922492
 
0.2%
21.287770042
 
0.2%
22.817460322
 
0.2%
20.661157022
 
0.2%
19.887258852
 
0.2%
20.861119662
 
0.2%
19.395918372
 
0.2%
24.241544492
 
0.2%
21.241004922
 
0.2%
24.394463672
 
0.2%
Other values (1006)1033
98.1%
ValueCountFrequency (%)
15.269471081
0.1%
15.338972351
0.1%
15.377500291
0.1%
15.445162251
0.1%
15.480864371
0.1%
15.495867771
0.1%
15.50173011
0.1%
15.515143321
0.1%
15.561339971
0.1%
15.637645971
0.1%
ValueCountFrequency (%)
49.67281381
0.1%
47.498964961
0.1%
47.199265381
0.1%
47.075962541
0.1%
45.800944981
0.1%
45.28925621
0.1%
44.90195341
0.1%
44.708956311
0.1%
43.490608141
0.1%
40.731875531
0.1%

study_week
Unsupported

Missing  Rejected  Unsupported 

Missing1053
Missing (%)100.0%
Memory size16.5 KiB

cd4_count_cells_uL
Real number (ℝ)

High correlation 

Distinct903
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.014084
Minimum0.26
Maximum54.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.394349image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.26
5-th percentile3.792
Q111.28
median17.08
Q323.62
95-th percentile34.336
Maximum54.13
Range53.87
Interquartile range (IQR)12.34

Descriptive statistics

Standard deviation9.1601515
Coefficient of variation (CV)0.50849944
Kurtosis-0.0048244797
Mean18.014084
Median Absolute Deviation (MAD)6.21
Skewness0.44891061
Sum18968.83
Variance83.908375
MonotonicityNot monotonic
2025-11-25T08:48:57.445867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.544
 
0.4%
22.684
 
0.4%
17.673
 
0.3%
16.53
 
0.3%
14.993
 
0.3%
5.583
 
0.3%
12.843
 
0.3%
16.933
 
0.3%
10.493
 
0.3%
17.743
 
0.3%
Other values (893)1021
97.0%
ValueCountFrequency (%)
0.261
0.1%
0.341
0.1%
0.451
0.1%
0.531
0.1%
0.631
0.1%
0.651
0.1%
0.71
0.1%
0.771
0.1%
0.831
0.1%
0.911
0.1%
ValueCountFrequency (%)
54.131
0.1%
50.631
0.1%
481
0.1%
44.711
0.1%
44.651
0.1%
44.611
0.1%
43.651
0.1%
43.071
0.1%
42.381
0.1%
41.451
0.1%

hiv_vl_copies_mL
Real number (ℝ)

High correlation 

Distinct977
Distinct (%)93.0%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean88703.72
Minimum0
Maximum4117370
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.495618image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile971.5
Q15839.5
median24796
Q379879
95-th percentile361649.5
Maximum4117370
Range4117370
Interquartile range (IQR)74039.5

Descriptive statistics

Standard deviation231648.72
Coefficient of variation (CV)2.6114882
Kurtosis117.98199
Mean88703.72
Median Absolute Deviation (MAD)21970
Skewness8.9610023
Sum93227610
Variance5.3661128 × 1010
MonotonicityNot monotonic
2025-11-25T08:48:57.542633image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
839803
 
0.3%
39553
 
0.3%
120493
 
0.3%
6412
 
0.2%
8892
 
0.2%
3763632
 
0.2%
375252
 
0.2%
36922
 
0.2%
1071472
 
0.2%
7652
 
0.2%
Other values (967)1028
97.6%
ValueCountFrequency (%)
01
0.1%
5011
0.1%
5051
0.1%
5121
0.1%
5271
0.1%
5281
0.1%
5351
0.1%
5411
0.1%
5531
0.1%
5561
0.1%
ValueCountFrequency (%)
41173701
0.1%
27572981
0.1%
23246901
0.1%
17604591
0.1%
15519881
0.1%
13932131
0.1%
12039331
0.1%
11350111
0.1%
11103452
0.2%
10005911
0.1%

hemoglobin_g_dL
Real number (ℝ)

High correlation 

Distinct103
Distinct (%)9.8%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean13.298669
Minimum6.1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.588918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum6.1
5-th percentile9.9
Q112.3
median13.4
Q314.6
95-th percentile16.1
Maximum18
Range11.9
Interquartile range (IQR)2.3

Descriptive statistics

Standard deviation1.8591093
Coefficient of variation (CV)0.13979664
Kurtosis0.50078028
Mean13.298669
Median Absolute Deviation (MAD)1.2
Skewness-0.54074656
Sum13990.2
Variance3.4562875
MonotonicityNot monotonic
2025-11-25T08:48:57.641361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.432
 
3.0%
12.530
 
2.8%
13.928
 
2.7%
13.827
 
2.6%
13.325
 
2.4%
13.524
 
2.3%
13.224
 
2.3%
13.624
 
2.3%
14.424
 
2.3%
14.723
 
2.2%
Other values (93)791
75.1%
ValueCountFrequency (%)
6.11
 
0.1%
6.81
 
0.1%
7.21
 
0.1%
7.31
 
0.1%
7.41
 
0.1%
7.61
 
0.1%
7.73
0.3%
7.91
 
0.1%
83
0.3%
8.21
 
0.1%
ValueCountFrequency (%)
181
0.1%
17.81
0.1%
17.61
0.1%
17.51
0.1%
17.41
0.1%
17.32
0.2%
17.21
0.1%
17.11
0.1%
172
0.2%
16.92
0.2%

hematocrit_percent
Real number (ℝ)

High correlation 

Distinct39
Distinct (%)3.7%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean40.671958
Minimum21
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.688426image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile31
Q137
median41
Q344
95-th percentile49
Maximum54
Range33
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.326574
Coefficient of variation (CV)0.13096429
Kurtosis0.29229504
Mean40.671958
Median Absolute Deviation (MAD)3
Skewness-0.47071382
Sum42786.9
Variance28.372391
MonotonicityNot monotonic
2025-11-25T08:48:57.735165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
4289
 
8.5%
4188
 
8.4%
4381
 
7.7%
4080
 
7.6%
4571
 
6.7%
3967
 
6.4%
3765
 
6.2%
4464
 
6.1%
3856
 
5.3%
3650
 
4.7%
Other values (29)341
32.4%
ValueCountFrequency (%)
211
 
0.1%
232
 
0.2%
254
 
0.4%
266
 
0.6%
273
 
0.3%
287
0.7%
2914
1.3%
3013
1.2%
3117
1.6%
3214
1.3%
ValueCountFrequency (%)
544
 
0.4%
531
 
0.1%
521
 
0.1%
516
 
0.6%
5027
2.6%
4920
1.9%
4837
3.5%
47.81
 
0.1%
4742
4.0%
4642
4.0%

wbc_count_10e9_L
Real number (ℝ)

High correlation 

Distinct496
Distinct (%)47.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean5.261635
Minimum1.52
Maximum24.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.781851image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.52
5-th percentile2.9455
Q14.0475
median4.95
Q36.1
95-th percentile8.6335
Maximum24.68
Range23.16
Interquartile range (IQR)2.0525

Descriptive statistics

Standard deviation1.9325762
Coefficient of variation (CV)0.36729576
Kurtosis13.505495
Mean5.261635
Median Absolute Deviation (MAD)1.03
Skewness2.3037535
Sum5535.24
Variance3.7348508
MonotonicityNot monotonic
2025-11-25T08:48:57.830480image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.478
 
0.8%
4.058
 
0.8%
5.77
 
0.7%
4.957
 
0.7%
4.477
 
0.7%
4.757
 
0.7%
5.596
 
0.6%
5.16
 
0.6%
4.086
 
0.6%
4.076
 
0.6%
Other values (486)984
93.4%
ValueCountFrequency (%)
1.521
0.1%
1.711
0.1%
1.821
0.1%
1.851
0.1%
1.941
0.1%
2.141
0.1%
2.171
0.1%
2.191
0.1%
2.221
0.1%
2.231
0.1%
ValueCountFrequency (%)
24.681
0.1%
17.961
0.1%
15.781
0.1%
15.331
0.1%
14.81
0.1%
13.211
0.1%
13.031
0.1%
12.421
0.1%
12.071
0.1%
11.931
0.1%

platelet_count_10e9_L
Real number (ℝ)

Distinct306
Distinct (%)29.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean265.84791
Minimum7
Maximum884
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.878302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile160.55
Q1214
median258
Q3303
95-th percentile409
Maximum884
Range877
Interquartile range (IQR)89

Descriptive statistics

Standard deviation82.110469
Coefficient of variation (CV)0.30886257
Kurtosis5.8713216
Mean265.84791
Median Absolute Deviation (MAD)44
Skewness1.3912982
Sum279672
Variance6742.1291
MonotonicityNot monotonic
2025-11-25T08:48:57.925675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26113
 
1.2%
21611
 
1.0%
24010
 
0.9%
28710
 
0.9%
2129
 
0.9%
2669
 
0.9%
2229
 
0.9%
2449
 
0.9%
2199
 
0.9%
2819
 
0.9%
Other values (296)954
90.6%
ValueCountFrequency (%)
71
0.1%
171
0.1%
421
0.1%
631
0.1%
801
0.1%
821
0.1%
871
0.1%
901
0.1%
961
0.1%
982
0.2%
ValueCountFrequency (%)
8841
0.1%
7511
0.1%
6761
0.1%
6521
0.1%
6191
0.1%
5751
0.1%
5521
0.1%
5491
0.1%
5441
0.1%
5421
0.1%

neutrophil_count_10e9_L
Real number (ℝ)

High correlation 

Distinct393
Distinct (%)37.5%
Missing6
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean2.7616619
Minimum0.19
Maximum9.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:57.972121image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.19
5-th percentile1.25
Q11.88
median2.52
Q33.35
95-th percentile5.311
Maximum9.31
Range9.12
Interquartile range (IQR)1.47

Descriptive statistics

Standard deviation1.2519029
Coefficient of variation (CV)0.45331506
Kurtosis2.9788724
Mean2.7616619
Median Absolute Deviation (MAD)0.68
Skewness1.4142769
Sum2891.46
Variance1.5672609
MonotonicityNot monotonic
2025-11-25T08:48:58.020259image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.668
 
0.8%
1.858
 
0.8%
3.728
 
0.8%
2.648
 
0.8%
2.368
 
0.8%
2.717
 
0.7%
2.497
 
0.7%
2.27
 
0.7%
2.157
 
0.7%
1.937
 
0.7%
Other values (383)972
92.3%
ValueCountFrequency (%)
0.191
0.1%
0.652
0.2%
0.721
0.1%
0.811
0.1%
0.862
0.2%
0.91
0.1%
0.922
0.2%
0.962
0.2%
0.992
0.2%
11
0.1%
ValueCountFrequency (%)
9.311
0.1%
9.171
0.1%
8.521
0.1%
8.071
0.1%
7.961
0.1%
7.661
0.1%
7.431
0.1%
7.41
0.1%
71
0.1%
6.991
0.1%

lymphocyte_count_10e9_L
Real number (ℝ)

High correlation 

Distinct295
Distinct (%)28.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.8269962
Minimum0.21
Maximum9.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.067802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.21
5-th percentile0.81
Q11.3
median1.73
Q32.24
95-th percentile3.1645
Maximum9.94
Range9.73
Interquartile range (IQR)0.94

Descriptive statistics

Standard deviation0.77925427
Coefficient of variation (CV)0.42652211
Kurtosis12.036719
Mean1.8269962
Median Absolute Deviation (MAD)0.47
Skewness1.8291566
Sum1922
Variance0.60723721
MonotonicityNot monotonic
2025-11-25T08:48:58.204078image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8211
 
1.0%
1.5911
 
1.0%
1.5811
 
1.0%
1.811
 
1.0%
1.5311
 
1.0%
1.3311
 
1.0%
1.9311
 
1.0%
1.6610
 
0.9%
1.6110
 
0.9%
1.4410
 
0.9%
Other values (285)945
89.7%
ValueCountFrequency (%)
0.211
 
0.1%
0.221
 
0.1%
0.251
 
0.1%
0.271
 
0.1%
0.331
 
0.1%
0.372
0.2%
0.451
 
0.1%
0.463
0.3%
0.471
 
0.1%
0.491
 
0.1%
ValueCountFrequency (%)
9.941
0.1%
5.921
0.1%
5.321
0.1%
4.731
0.1%
4.681
0.1%
4.211
0.1%
4.21
0.1%
4.161
0.1%
4.141
0.1%
4.111
0.1%

monocyte_count_10e9_L
Real number (ℝ)

High correlation 

Distinct96
Distinct (%)9.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.4538308
Minimum0.11
Maximum2.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.249731image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.11
5-th percentile0.22
Q10.33
median0.42
Q30.54
95-th percentile0.79
Maximum2.12
Range2.01
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.19087226
Coefficient of variation (CV)0.42058022
Kurtosis10.270507
Mean0.4538308
Median Absolute Deviation (MAD)0.1
Skewness2.0631299
Sum477.43
Variance0.036432219
MonotonicityNot monotonic
2025-11-25T08:48:58.302040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4333
 
3.1%
0.3433
 
3.1%
0.4132
 
3.0%
0.431
 
2.9%
0.3830
 
2.8%
0.3630
 
2.8%
0.3529
 
2.8%
0.4829
 
2.8%
0.2928
 
2.7%
0.4628
 
2.7%
Other values (86)749
71.1%
ValueCountFrequency (%)
0.114
 
0.4%
0.122
 
0.2%
0.143
 
0.3%
0.154
 
0.4%
0.163
 
0.3%
0.171
 
0.1%
0.186
0.6%
0.194
 
0.4%
0.26
0.6%
0.2112
1.1%
ValueCountFrequency (%)
2.121
0.1%
1.841
0.1%
1.541
0.1%
1.471
0.1%
1.421
0.1%
1.181
0.1%
1.171
0.1%
1.081
0.1%
1.072
0.2%
1.041
0.1%

eosinophil_count_10e9_L
Real number (ℝ)

Zeros 

Distinct88
Distinct (%)8.4%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.14214829
Minimum0
Maximum3.16
Zeros47
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.352066image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.03
median0.075
Q30.16
95-th percentile0.51
Maximum3.16
Range3.16
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.22564749
Coefficient of variation (CV)1.5874091
Kurtosis44.797394
Mean0.14214829
Median Absolute Deviation (MAD)0.055
Skewness5.3004426
Sum149.54
Variance0.050916789
MonotonicityNot monotonic
2025-11-25T08:48:58.400739image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0187
 
8.3%
0.0285
 
8.1%
0.0370
 
6.6%
0.0762
 
5.9%
0.0459
 
5.6%
0.0659
 
5.6%
0.0557
 
5.4%
047
 
4.5%
0.0844
 
4.2%
0.1240
 
3.8%
Other values (78)442
42.0%
ValueCountFrequency (%)
047
4.5%
0.0187
8.3%
0.0285
8.1%
0.0370
6.6%
0.0459
5.6%
0.0557
5.4%
0.0659
5.6%
0.0762
5.9%
0.0844
4.2%
0.0937
3.5%
ValueCountFrequency (%)
3.161
0.1%
1.891
0.1%
1.752
0.2%
1.571
0.1%
1.511
0.1%
1.481
0.1%
1.351
0.1%
1.251
0.1%
1.232
0.2%
1.151
0.1%

basophil_count_10e9_L
Real number (ℝ)

Zeros 

Distinct15
Distinct (%)1.4%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.024030418
Minimum0
Maximum0.21
Zeros122
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.444151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01
median0.02
Q30.03
95-th percentile0.05
Maximum0.21
Range0.21
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.019359659
Coefficient of variation (CV)0.80563139
Kurtosis13.357364
Mean0.024030418
Median Absolute Deviation (MAD)0.01
Skewness2.4211104
Sum25.28
Variance0.00037479641
MonotonicityNot monotonic
2025-11-25T08:48:58.481835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.02293
27.8%
0.03217
20.6%
0.01217
20.6%
0122
11.6%
0.04100
 
9.5%
0.0551
 
4.8%
0.0619
 
1.8%
0.0712
 
1.1%
0.096
 
0.6%
0.085
 
0.5%
Other values (5)10
 
0.9%
ValueCountFrequency (%)
0122
11.6%
0.01217
20.6%
0.02293
27.8%
0.03217
20.6%
0.04100
 
9.5%
0.0551
 
4.8%
0.0619
 
1.8%
0.0712
 
1.1%
0.085
 
0.5%
0.096
 
0.6%
ValueCountFrequency (%)
0.211
 
0.1%
0.161
 
0.1%
0.132
 
0.2%
0.114
 
0.4%
0.12
 
0.2%
0.096
 
0.6%
0.085
 
0.5%
0.0712
 
1.1%
0.0619
 
1.8%
0.0551
4.8%

mcv_fL
Real number (ℝ)

High correlation 

Distinct286
Distinct (%)27.2%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean86.905228
Minimum58.1
Maximum103.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.526888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum58.1
5-th percentile73.455
Q183.6
median87.5
Q391.7
95-th percentile96.445
Maximum103.5
Range45.4
Interquartile range (IQR)8.1

Descriptive statistics

Standard deviation6.9486359
Coefficient of variation (CV)0.079956477
Kurtosis1.4099648
Mean86.905228
Median Absolute Deviation (MAD)4
Skewness-0.87892782
Sum91424.3
Variance48.283541
MonotonicityNot monotonic
2025-11-25T08:48:58.574969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.513
 
1.2%
87.313
 
1.2%
89.312
 
1.1%
8812
 
1.1%
90.411
 
1.0%
89.110
 
0.9%
91.710
 
0.9%
84.710
 
0.9%
85.210
 
0.9%
86.910
 
0.9%
Other values (276)941
89.4%
ValueCountFrequency (%)
58.11
0.1%
59.71
0.1%
601
0.1%
60.11
0.1%
60.91
0.1%
61.21
0.1%
61.81
0.1%
62.11
0.1%
62.51
0.1%
63.31
0.1%
ValueCountFrequency (%)
103.52
0.2%
102.31
0.1%
101.81
0.1%
100.81
0.1%
100.71
0.1%
100.61
0.1%
100.51
0.1%
100.31
0.1%
99.81
0.1%
99.71
0.1%

mch_pg
Real number (ℝ)

High correlation 

Distinct138
Distinct (%)13.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean28.411597
Minimum16.7
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.620676image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum16.7
5-th percentile23.1
Q127.1
median28.7
Q330.3
95-th percentile32.145
Maximum34
Range17.3
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.7248789
Coefficient of variation (CV)0.095907279
Kurtosis1.4802156
Mean28.411597
Median Absolute Deviation (MAD)1.6
Skewness-0.94437237
Sum29889
Variance7.4249653
MonotonicityNot monotonic
2025-11-25T08:48:58.670392image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.625
 
2.4%
29.921
 
2.0%
28.921
 
2.0%
28.821
 
2.0%
27.920
 
1.9%
29.420
 
1.9%
27.519
 
1.8%
27.718
 
1.7%
27.218
 
1.7%
27.318
 
1.7%
Other values (128)851
80.8%
ValueCountFrequency (%)
16.71
0.1%
17.31
0.1%
17.61
0.1%
17.81
0.1%
17.91
0.1%
18.21
0.1%
18.41
0.1%
18.51
0.1%
18.81
0.1%
19.71
0.1%
ValueCountFrequency (%)
341
 
0.1%
33.91
 
0.1%
33.82
0.2%
33.71
 
0.1%
33.53
0.3%
33.42
0.2%
33.34
0.4%
33.21
 
0.1%
33.12
0.2%
332
0.2%

mchc_g_dL
Real number (ℝ)

High correlation 

Distinct59
Distinct (%)5.6%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean32.653707
Minimum28.3
Maximum35.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.5 KiB
2025-11-25T08:48:58.721677image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum28.3
5-th percentile31.2
Q132.2
median32.7
Q333.2
95-th percentile33.9
Maximum35.9
Range7.6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.89265719
Coefficient of variation (CV)0.027337086
Kurtosis2.0274307
Mean32.653707
Median Absolute Deviation (MAD)0.5
Skewness-0.58209633
Sum34351.7
Variance0.79683686
MonotonicityNot monotonic
2025-11-25T08:48:58.773916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.660
 
5.7%
32.757
 
5.4%
32.454
 
5.1%
33.154
 
5.1%
3353
 
5.0%
33.252
 
4.9%
32.551
 
4.8%
32.850
 
4.7%
32.946
 
4.4%
32.344
 
4.2%
Other values (49)531
50.4%
ValueCountFrequency (%)
28.31
0.1%
28.61
0.1%
28.71
0.1%
28.81
0.1%
29.32
0.2%
29.41
0.1%
29.81
0.1%
302
0.2%
30.21
0.1%
30.32
0.2%
ValueCountFrequency (%)
35.91
 
0.1%
35.61
 
0.1%
35.31
 
0.1%
352
 
0.2%
34.94
 
0.4%
34.72
 
0.2%
34.61
 
0.1%
34.53
 
0.3%
34.410
0.9%
34.33
 
0.3%

Interactions

2025-11-25T08:48:56.178893image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.392421image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.023598image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.592519image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.143415image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.771923image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.332825image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.900272image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.444732image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.061747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.600961image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.150760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.837498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.488366image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.085419image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.622953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.212812image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.438839image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.056829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.625341image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.176415image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.803515image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.365484image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.931795image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.476482image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.093732image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.634494image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.185203image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.872171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.520202image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.118428image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.656550image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.251165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.500014image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.091631image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.664987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.211165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.838780image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.402494image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.968261image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.511530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.127925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.670850image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.306367image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.908354image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.556673image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.154760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.693791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.287086image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.548525image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.126267image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.697040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.245964image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.873760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.436482image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.999861image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.544483image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.161360image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.704218image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.365083image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.942988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.589529image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.187029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.727880image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.321859image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.602548image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.159410image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.728935image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.277191image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.907393image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.470084image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.033826image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.576227image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.193793image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.738528image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.403806image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.977217image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.671271image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.219639image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.762886image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.357048image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.641899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.196544image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.763896image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.311989image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.942035image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.506628image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.067031image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.611957image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.225914image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.773548image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.439950image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.013906image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.707903image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.253122image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.799202image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.395281image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.694248image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.233172image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.800095image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.347087image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.978552image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.544714image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.102355image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.647690image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.263754image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.810481image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.478701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.052675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.744964image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.288782image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.835309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.428788image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.726545image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.270477image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.832751image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.378555image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.012781image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.578530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.134231image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.679038image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.299972image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.841914image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.512910image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.086134image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.778297image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.320471image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.868454image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.463183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.758026image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.303946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.864437image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.410296image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.045261image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.612827image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.166796image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.710730image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.332461image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.876128image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.548923image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.120746image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.810053image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.352993image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.901939image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.497885image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.788748image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.337542image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.896004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.442711image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.077247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.648073image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.201439image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.742018image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.363851image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.907850image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.581572image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.153883image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.842917image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.384710image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.935238image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.533257image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.821898image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.372945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.930706image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.477130image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.113656image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.682416image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.234870image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.777441image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.397359image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.939930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.616456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.190561image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.877032image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.417871image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.967892image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.570868image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.856963image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.410569image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.968232image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.512326image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.150646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.721317image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.272621image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.813306image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.431657image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.978115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.655011image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.228004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.913309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.454824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.005692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.608920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.892352image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.448261image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.004499image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.547163image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.188916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.758051image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.311033image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.847711image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.466789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.013221image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.691183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.262691image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.948939image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.488704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.040224image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.644190image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.923585image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.482661image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.038433image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.668728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.222323image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.792954image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.342655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.961841image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.500347image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.046615image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.728061image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.380321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.981431image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.521722image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.073747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.678668image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.953920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.516802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.072209image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.700632image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.257803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.825530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.374290image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.992695image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.530856image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.078903image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.760372image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.413722image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.013386image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.551497image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.105794image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.797047image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:47.988187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:48.552852image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.106334image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:49.735780image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.293959image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:50.861075image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:51.408051image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.025316image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:52.565103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.114151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:53.797421image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:54.451000image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.048855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:55.585266image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-11-25T08:48:56.139820image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2025-11-25T08:48:58.816084image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Age (at enrolment)BMI (kg/m²)Sexbasophil_count_10e9_Lcd4_count_cells_uLeosinophil_count_10e9_Lhematocrit_percenthemoglobin_g_dLhiv_vl_copies_mLlymphocyte_count_10e9_Lmch_pgmchc_g_dLmcv_fLmonocyte_count_10e9_Lneutrophil_count_10e9_Lplatelet_count_10e9_Lwbc_count_10e9_L
Age (at enrolment)1.0000.1630.1420.009-0.1610.004-0.080-0.0720.054-0.1110.0510.0200.047-0.035-0.106-0.055-0.131
BMI (kg/m²)0.1631.0000.3630.0120.0870.004-0.121-0.111-0.1410.126-0.011-0.000-0.0160.0630.0550.0950.088
Sex0.1420.3631.0000.0000.0720.0370.5680.5670.0520.0670.1770.1730.1580.0000.0000.1740.017
basophil_count_10e9_L0.0090.0120.0001.0000.1180.1740.0750.066-0.1440.3900.021-0.0270.0390.2360.1830.1510.349
cd4_count_cells_uL-0.1610.0870.0720.1181.000-0.0190.1740.170-0.5070.1820.1050.0340.110-0.0540.1640.0650.179
eosinophil_count_10e9_L0.0040.0040.0370.174-0.0191.0000.0530.0520.0550.1250.0540.0090.0580.079-0.0350.0020.115
hematocrit_percent-0.080-0.1210.5680.0750.1740.0531.0000.979-0.0930.1070.3330.2300.3260.0280.050-0.2210.088
hemoglobin_g_dL-0.072-0.1110.5670.0660.1700.0520.9791.000-0.0900.1020.4360.3920.3900.0250.051-0.2270.085
hiv_vl_copies_mL0.054-0.1410.052-0.144-0.5070.055-0.093-0.0901.000-0.246-0.0030.032-0.0100.072-0.077-0.061-0.139
lymphocyte_count_10e9_L-0.1110.1260.0670.3900.1820.1250.1070.102-0.2461.0000.069-0.0050.0800.3570.1900.1380.624
mch_pg0.051-0.0110.1770.0210.1050.0540.3330.436-0.0030.0691.0000.6790.9600.005-0.015-0.1380.019
mchc_g_dL0.020-0.0000.173-0.0270.0340.0090.2300.3920.032-0.0050.6791.0000.476-0.026-0.029-0.137-0.025
mcv_fL0.047-0.0160.1580.0390.1100.0580.3260.390-0.0100.0800.9600.4761.0000.016-0.006-0.1180.030
monocyte_count_10e9_L-0.0350.0630.0000.236-0.0540.0790.0280.0250.0720.3570.005-0.0260.0161.0000.4390.1520.603
neutrophil_count_10e9_L-0.1060.0550.0000.1830.164-0.0350.0500.051-0.0770.190-0.015-0.029-0.0060.4391.0000.2550.837
platelet_count_10e9_L-0.0550.0950.1740.1510.0650.002-0.221-0.227-0.0610.138-0.138-0.137-0.1180.1520.2551.0000.258
wbc_count_10e9_L-0.1310.0880.0170.3490.1790.1150.0880.085-0.1390.6240.019-0.0250.0300.6030.8370.2581.000

Missing values

2025-11-25T08:48:56.852999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-11-25T08:48:56.950701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-11-25T08:48:57.033534image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Age (at enrolment)SexBMI (kg/m²)study_weekcd4_count_cells_uLhiv_vl_copies_mLhemoglobin_g_dLhematocrit_percentwbc_count_10e9_Lplatelet_count_10e9_Lneutrophil_count_10e9_Llymphocyte_count_10e9_Lmonocyte_count_10e9_Leosinophil_count_10e9_Lbasophil_count_10e9_Lmcv_fLmch_pgmchc_g_dL
216230.0Male23.916239NaN35.06641.014.846.05.89294.03.601.830.370.060.0282.526.331.9
216334.0Male27.645308NaN28.023851.014.343.02.90261.01.361.260.240.020.0289.729.532.9
216444.0Male23.836248NaN25.758961.016.650.04.50216.01.792.070.450.100.0992.330.433.0
216525.0Female45.289256NaN25.85903.012.138.05.70281.02.822.330.440.060.0484.426.531.4
216620.0Female28.664018NaN12.4815081.012.037.05.55188.01.771.970.421.350.0390.229.432.6
216733.0Female30.859375NaN32.59680.013.540.05.67239.03.321.660.560.110.0390.530.433.6
216823.0Female20.870053NaN41.4512806.014.042.03.90238.02.461.190.200.040.0085.828.433.0
216930.0Female23.555556NaN8.81179182.010.131.02.19266.01.120.710.270.070.0382.127.032.8
217023.0Female31.953125NaN25.4010611.010.733.03.01260.01.521.090.320.060.0276.224.532.2
217120.0Female18.850387NaN17.89443901.011.637.03.62154.00.652.680.290.000.0084.526.731.6
Age (at enrolment)SexBMI (kg/m²)study_weekcd4_count_cells_uLhiv_vl_copies_mLhemoglobin_g_dLhematocrit_percentwbc_count_10e9_Lplatelet_count_10e9_Lneutrophil_count_10e9_Llymphocyte_count_10e9_Lmonocyte_count_10e9_Leosinophil_count_10e9_Lbasophil_count_10e9_Lmcv_fLmch_pgmchc_g_dL
320518.0Female31.092612NaN18.192461.013.941.04.95249.01.932.620.320.030.0591.130.533.4
320618.0Male15.515143NaN2.6777566.012.941.03.04278.01.511.110.200.210.0175.923.931.5
320715.0Male17.998028NaN2.86361889.012.638.06.29216.02.912.740.480.110.0581.026.833.1
320818.0Male20.408163NaN27.5251443.016.449.04.42312.02.611.260.520.020.0284.628.333.4
320918.0Female29.658625NaN6.908022.013.039.05.81384.02.232.780.380.390.0380.626.633.1
321018.0Male20.451963NaN14.611295.014.745.08.31193.05.242.390.630.020.0386.628.532.9
321117.0Male18.800472NaN18.437856.015.345.04.47261.02.621.360.370.100.0287.329.433.7
321218.0Female21.693141NaN34.9126688.013.341.03.79272.01.422.100.150.100.0293.530.732.8
321315.0Female22.247230NaN0.63170902.012.237.03.38231.02.360.220.310.490.0088.728.932.6
321418.0Female24.728984NaN23.6861862.011.737.04.84344.02.192.160.410.070.0287.227.431.5